We implement a tree-to-tree encoder/decoder model patterned off [1]}. The tree encoder is almost identical to the one described in the paper except that our model does not use dropout [2]} as we did not find it improved training accuracy. However, we modify their tree decoder to make use of the grammar of the target language when generating nodes. Unlike in the paper by Chen et al., we do not binarize the output tree, because the target language's grammar rules cannot easily be applied to trees in which a node's siblings can appear as its children.
